from easydict import EasyDict as edict
import os
import torch
__c = edict()
cfg = __c

__c.net = "TFComp" #DNNWithBN, DNNWithLN,
# TFClassifierForwardLinear, TFClassifierForwardEmbedding  TransformerComp

__c.layer_norm = False

if "TF" in __c.net:
    __c.d_model = 128  #词嵌入向量的大小
    __c.num_layers = 4
    __c.num_heads = 4
    __c.dropout_rate = 0.2

__c.word_dict_size = 5000
__c.output_dim = 1

__c.learning_rate = 0.001
__c.epochs = 10
__c.batch_size = 100
__c.test_size = 0.01

__c.max_model_count = 100 #训练模型数（针对不同用户）
__c.data_row_size = 16  #标准化后数据的行大小
__c.step = 16  #标准化时，滑动窗口大小
__c.copy_size = 500  #正样本重复度

__c.show_roc = False

# path
dir_head = os.getcwd()
__c.dataPath = "/data/DatabaseSample/"
__c.validDataFile = "processed-valid-data.csv"
__c.invalidDataFile = "processed-invalid-data.csv"
__c.user_data_file_name = "x_data.csv"
__c.user_id_file_name = "y_data.csv"
__c.save_model_path = "/model/model_result/"

__c.user_data_file_path = dir_head + __c.dataPath + __c.user_data_file_name
__c.user_id_file_path = dir_head + __c.dataPath + __c.user_id_file_name

#===================================================================================
